Stabilizing the Proteomes of Acute Myeloid Leukemia Cells: Implications for Cancer Proteomics.

Previous work has shown that inhibition of abundant myeloid azurophil granule-associated serine proteases (ELANE [neutrophil elastase], PRTN3 [protease 3], and CTSG [Cathepsin G]) is required to stabilize some proteins in myeloid cells. We therefore hypothesized that effective inhibition of these proteases may be necessary for quantitative proteomic analysis of samples containing myeloid cells. To test this hypothesis, we thawed viably preserved acute myeloid leukemia cells from cryovials in the presence or the absence of diisopropyl fluorophosphate (DFP), a cell-permeable and irreversible serine protease inhibitor. Global proteomic analysis was performed, using label-free and isobaric peptide-labeling quantitation. The presence of DFP resulted in an increase of tryptic peptides (14-57%) and proteins (9-31%). In the absence of DFP, 11 to 31% of peptide intensity came from nontryptic peptides; 52 to 75% had cleavage specificity consistent with activities of ELANE-PRTN3. Treatment with DFP reduced the intensity of nontryptic peptides to 4-8% of the total. ELANE inhibition was 95%, based on diisopropyl phosphate modification of active site serine residue. Overall, the relative abundance of 20% of proteins was significantly altered by DFP treatment. These results suggest that active myeloid serine proteases, released during sample processing, can skew quantitative proteomic measurements. Finally, significant ELANE activity was also detected in Clinical Proteomics Tumor Analysis Consortium datasets of solid tumors (many of which have known myeloid infiltration). In the pancreatic cancer dataset, the median percentage of nontryptic intensity detected across patient samples was 34%, with many patient samples having more than half of their detected peptide intensity from nontryptic cleavage events consistent with ELANE-PRTN3 cleavage specificity. Our study suggests that in vitro cleavage of proteins by myeloid serine proteases may be relevant for proteomic studies of any tumor that contains infiltrating myeloid cells.

Direct Proteomic Detection and Prioritization of 19 Onchocerciasis Biomarker Candidates in Humans.

Onchocerca volvulus, the causative agent of onchocerciasis, infects over 20 million people and can cause severe dermatitis and ocular conditions including blindness. Current treatments employed in mass drug administration programs do not kill adult female worms, and common diagnostic tests cannot reliably assess viability of adult worms. There is an urgent need for better diagnostic tests to facilitate monitoring the efficacy of new treatments and disease elimination efforts. Here, eight plasma samples collected from individuals infected with O. volvulus and seven from uninfected individuals were analyzed by MS/MS spectrometry to directly identify O. volvulus proteins present in infected but absent in uninfected control samples. This direct proteomic approach for biomarker discovery had not been previously employed for onchocerciasis. Among all detected proteins, 19 biomarker candidates were supported by two or more unique peptides, identified in the plasma of at least three O. volvulus-infected human samples and absent in all control samples. Comprehensive analysis and ranking of these candidates included detailed functional annotation and a review of RNA-seq gene expression profiles. Isotope-labeled standard peptides were run in parallel and validated MS/MS peptide identifications for 15 peptides from 11 of the 19 proteins, and two infected urine and one uninfected urine sample was used for additional validation. A major antigen/OVOC11613 was identified as the most promising candidate with eight unique peptides across five plasma samples and one urine sample. Additional strong candidates included OVOC1523/ATP synthase, OVOC247/laminin and OVOC11626/PLK5, and along with OVOC11613, and were also detected in urine samples from onchocerciasis patients. This study has identified a promising novel set of proteins that will be carried forward to develop assays that can be used for diagnosis of O. volvulus infections and for monitoring treatment efficacy.

Protein Kinase Signaling Networks Driven by Oncogenic Gq/11 in Uveal Melanoma Identified by Phosphoproteomic and Bioinformatic Analyses.

Metastatic uveal melanoma (UM) patients typically survive only 2 to 3 years because effective therapy does not yet exist. Here, to facilitate the discovery of therapeutic targets in UM, we have identified protein kinase signaling mechanisms elicited by the drivers in 90% of UM tumors: mutant constitutively active G protein α-subunits encoded by GNAQ (Gq) or GNA11 (G11). We used the highly specific Gq/11 inhibitor FR900359 (FR) to elucidate signaling networks that drive proliferation, metabolic reprogramming, and dedifferentiation of UM cells. We determined the effects of FR on the proteome and phosphoproteome of UM cells as indicated by bioinformatic analyses with CausalPath and site-specific gene set enrichment analysis. We found that inhibition of oncogenic Gq/11 caused deactivation of PKC, Erk, and the cyclin-dependent kinases CDK1 and CDK2 that drive proliferation. Inhibition of oncogenic Gq/11 in UM cells with low metastatic risk relieved inhibitory phosphorylation of polycomb-repressive complex subunits that regulate melanocytic redifferentiation. Site-specific gene set enrichment analysis, unsupervised analysis, and functional studies indicated that mTORC1 and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 2 drive metabolic reprogramming in UM cells. Together, these results identified protein kinase signaling networks driven by oncogenic Gq/11 that regulate critical aspects of UM cell biology and provide targets for therapeutic investigation.

Proteins in Tumor-Derived Plasma Extracellular Vesicles Indicate Tumor Origin.

Cancer-derived extracellular vesicles (EVs) promote tumorigenesis, premetastatic niche formation, and metastasis via their protein cargo. However, the proteins packaged by patient tumors into EVs cannot be determined in vivo because of the presence of EVs derived from other tissues. We therefore developed a cross-species proteomic method to quantify the human tumor-derived proteome of plasma EVs produced by patient-derived xenografts of four cancer types. Proteomic profiling revealed individualized packaging of novel protein cargo, and machine learning accurately classified the type of the underlying tumor.

Proteomic and phosphoproteomic landscapes of acute myeloid leukemia.

We have developed a deep-scale proteome and phosphoproteome database from 44 representative acute myeloid leukemia (AML) patients from the LAML TCGA dataset and 6 healthy bone marrow-derived controls. After confirming data quality, we orthogonally validated several previously undescribed features of AML revealed by the proteomic data. We identified examples of posttranscriptionally regulated proteins both globally (ie, in all AML samples) and also in patients with recurrent AML driver mutations. For example, samples with IDH1/2 mutations displayed elevated levels of the 2-oxoglutarate-dependent histone demethylases KDM4A/B/C, despite no changes in messenger RNA levels for these genes; we confirmed this finding in vitro. In samples with NPMc mutations, we identified several nuclear importins with posttranscriptionally increased protein abundance and showed that they interact with NPMc but not wild-type NPM1. We identified 2 cell surface proteins (CD180 and MRC1/CD206) expressed on AML blasts of many patients (but not healthy CD34+ stem/progenitor cells) that could represent novel targets for immunologic therapies and confirmed these targets via flow cytometry. Finally, we detected nearly 30 000 phosphosites in these samples; globally, AML samples were associated with the abnormal phosphorylation of specific residues in PTPN11, STAT3, AKT1, and PRKCD. FLT3-TKD samples were associated with increased phosphorylation of activating tyrosines on the cytoplasmic Src-family tyrosine kinases FGR and HCK and related signaling proteins. PML-RARA-initiated AML samples displayed a unique phosphorylation signature, and TP53-mutant samples showed abundant phosphorylation of serine-183 on TP53 itself. This publicly available database will serve as a foundation for further investigations of protein dysregulation in AML pathogenesis.

Proteogenomics connects somatic mutations to signalling in breast cancer.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Regulated Phosphosignaling Associated with Breast Cancer Subtypes and Druggability.

Aberrant phospho-signaling is a hallmark of cancer. We investigated kinase-substrate regulation of 33,239 phosphorylation sites (phosphosites) in 77 breast tumors and 24 breast cancer xenografts. Our search discovered 2134 quantitatively correlated kinase-phosphosite pairs, enriching for and extending experimental or binding-motif predictions. Among the 91 kinases with auto-phosphorylation, elevated EGFR, ERBB2, PRKG1, and WNK1 phosphosignaling were enriched in basal, HER2-E, Luminal A, and Luminal B breast cancers, respectively, revealing subtype-specific regulation. CDKs, MAPKs, and ataxia-telangiectasia proteins were dominant, master regulators of substrate-phosphorylation, whose activities are not captured by genomic evidence. We unveiled phospho-signaling and druggable targets from 113 kinase-substrate pairs and cascades downstream of kinases, including AKT1, BRAF and EGFR. We further identified kinase-substrate-pairs associated with clinical or immune signatures and experimentally validated activated phosphosites of ERBB2, EIF4EBP1, and EGFR. Overall, kinase-substrate regulation revealed by the largest unbiased global phosphorylation data to date connects driver events to their signaling effects.

Proteogenomic characterization of human colon and rectal cancer.

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction.

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this "guilt-by-association" (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies.

Human Experimental Challenge With Enterotoxigenic Escherichia coli Elicits Immune Responses to Canonical and Novel Antigens Relevant to Vaccine Development.

Background: Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrheal illness in the developing world. Enterotoxigenic E coli vaccinology has been challenged by genetic diversity and heterogeneity of canonical antigens. Examination of the antigenic breadth of immune responses associated with protective immunity could afford new avenues for vaccine development. Methods: Antibody lymphocyte supernatants (ALS) and sera from 20 naive human volunteers challenged with ETEC strain H10407 and from 10 volunteers rechallenged 4-6 weeks later with the same strain (9 of whom were completely protected on rechallenge) were tested against ETEC proteome microarrays containing 957 antigens. Results: Enterotoxigenic E coli challenge stimulated robust serum and mucosal (ALS) responses to canonical vaccine antigens (CFA/I, and the B subunit of LT) as well as a small number of antigens not presently targeted in ETEC vaccines. These included pathovar-specific secreted proteins (EtpA, EatA) as well as highly conserved E coli antigens including YghJ, flagellin, and pertactin-like autotransporter proteins, all of which have previously afforded protection against ETEC infection in preclinical studies. Conclusions: Taken together, studies reported here suggest that immune responses after ETEC infection involve traditional vaccine targets as well as a select number of more recently identified protein antigens that could offer additional avenues for vaccine development for these pathogens.

C-terminal phosphorylation of NaV1.5 impairs FGF13-dependent regulation of channel inactivation.

Voltage-gated Na+ (NaV) channels are key regulators of myocardial excitability, and Ca2+/calmodulin-dependent protein kinase II (CaMKII)-dependent alterations in NaV1.5 channel inactivation are emerging as a critical determinant of arrhythmias in heart failure. However, the global native phosphorylation pattern of NaV1.5 subunits associated with these arrhythmogenic disorders and the associated channel regulatory defects remain unknown. Here, we undertook phosphoproteomic analyses to identify and quantify in situ the phosphorylation sites in the NaV1.5 proteins purified from adult WT and failing CaMKIIδc-overexpressing (CaMKIIδc-Tg) mouse ventricles. Of 19 native NaV1.5 phosphorylation sites identified, two C-terminal phosphoserines at positions 1938 and 1989 showed increased phosphorylation in the CaMKIIδc-Tg compared with the WT ventricles. We then tested the hypothesis that phosphorylation at these two sites impairs fibroblast growth factor 13 (FGF13)-dependent regulation of NaV1.5 channel inactivation. Whole-cell voltage-clamp analyses in HEK293 cells demonstrated that FGF13 increases NaV1.5 channel availability and decreases late Na+ current, two effects that were abrogated with NaV1.5 mutants mimicking phosphorylation at both sites. Additional co-immunoprecipitation experiments revealed that FGF13 potentiates the binding of calmodulin to NaV1.5 and that phosphomimetic mutations at both sites decrease the interaction of FGF13 and, consequently, of calmodulin with NaV1.5. Together, we have identified two novel native phosphorylation sites in the C terminus of NaV1.5 that impair FGF13-dependent regulation of channel inactivation and may contribute to CaMKIIδc-dependent arrhythmogenic disorders in failing hearts.

Integrated Bottom-Up and Top-Down Proteomics of Patient-Derived Breast Tumor Xenografts.

Bottom-up proteomics relies on the use of proteases and is the method of choice for identifying thousands of protein groups in complex samples. Top-down proteomics has been shown to be robust for direct analysis of small proteins and offers a solution to the "peptide-to-protein" inference problem inherent with bottom-up approaches. Here, we describe the first large-scale integration of genomic, bottom-up and top-down proteomic data for the comparative analysis of patient-derived mouse xenograft models of basal and luminal B human breast cancer, WHIM2 and WHIM16, respectively. Using these well-characterized xenograft models established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, we compared and contrasted the performance of bottom-up and top-down proteomics to detect cancer-specific aberrations at the peptide and proteoform levels and to measure differential expression of proteins and proteoforms. Bottom-up proteomic analysis of the tumor xenografts detected almost 10 times as many coding nucleotide polymorphisms and peptides resulting from novel splice junctions than top-down. For proteins in the range of 0-30 kDa, where quantitation was performed using both approaches, bottom-up proteomics quantified 3,519 protein groups from 49,185 peptides, while top-down proteomics quantified 982 proteoforms mapping to 358 proteins. Examples of both concordant and discordant quantitation were found in a ∼60:40 ratio, providing a unique opportunity for top-down to fill in missing information. The two techniques showed complementary performance, with bottom-up yielding eight times more identifications of 0-30 kDa proteins in xenograft proteomes, but failing to detect differences in certain posttranslational modifications (PTMs), such as phosphorylation pattern changes of alpha-endosulfine. This work illustrates the potency of a combined bottom-up and top-down proteomics approach to deepen our knowledge of cancer biology, especially when genomic data are available.

An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer.

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations, and splice variants identified in cancer cells are translated. Herein, we apply a proteogenomic data integration tool (QUILTS) to illustrate protein variant discovery using whole genome, whole transcriptome, and global proteome datasets generated from a pair of luminal and basal-like breast-cancer-patient-derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS sample process replicates defined here as an independent tandem MS experiment using identical sample material. Despite analysis of over 30 sample process replicates, only about 10% of SNVs (somatic and germline) detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNVs without a detectable mRNA transcript were also observed, suggesting that transcriptome coverage was incomplete (∼80%). In contrast to germline variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than in the luminal tumor, raising the possibility of differential translation or protein degradation effects. In conclusion, this large-scale proteogenomic integration allowed us to determine the degree to which mutations are translated and identify gaps in sequence coverage, thereby benchmarking current technology and progress toward whole cancer proteome and transcriptome analysis.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.

Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we derived a quantification confidence score based on the quality of each peptide-spectrum match to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS data sets collected over a 7-month period. This study provides the first quality assessment on long-term stability and technical considerations for study design of a large-scale clinical proteomics project.

Functional Consequences of Mannose and Asialoglycoprotein Receptor Ablation.

The mannose receptor (ManR, Mrc1) and asialoglycoprotein receptor (ASGR, Asgr1 and Asgr2) are highly abundant endocytic receptors expressed by sinusoidal endothelial cells and parenchymal cells in the liver, respectively. We genetically manipulated either receptor individually or in combination, revealing phenotypic changes in female and male mice associated with changes in circulating levels of many glycoproteins. Both receptors rise and fall in response to progesterone during pregnancy. Thirty percent of Asgr2(-/-) and 65% of Mrc1(-/-)Asgr2(-/-) mice are unable to initiate parturition at the end of pregnancy, whereas Mrc1(-/-) mice initiate normally. Twenty five percent of Mrc1(-/-)Asgr2(-/-) male mice develop priapism when mating due to thrombosis of the penile vein, but neither Mrc1(-/-) nor Asgr2(-/-) mice do so. The half-life for luteinizing hormone (LH) clearance increases in Mrc1(-/-) and Mrc1(-/-)Asgr2(-/-) mice but not in Asgr2(-/-) mice; however, LH and testosterone are elevated in all three knockouts. The ManR clears LH thus regulating testosterone production, whereas the ASGR appears to mediate clearance of an unidentified glycoprotein that increases LH levels. More than 40 circulating glycoproteins are elevated >3.0-fold in pregnant Mrc1(-/-)Asgr2(-/-) mice. Pregnancy-specific glycoprotein 23, undetectable in WT mice (<50 ng/ml plasma), reaches levels of 1-10 mg/ml in the plasma of Mrc1(-/-)Asgr2(-/-) and Asgr2(-/-) mice, indicating it is cleared by the ASGR. Elevation of multiple coagulation factors in Mrc1(-/-)Asgr2(-/-) mice may account for priapism seen in males. These male and female phenotypic changes underscore the key roles of the ManR and ASGR in controlling circulating levels of numerous glycoproteins critical for regulating reproductive hormones and blood coagulation.

An Integrated Multiomics Approach to Identify Candidate Antigens for Serodiagnosis of Human Onchocerciasis.

Improved diagnostic methods are needed to support ongoing efforts to eliminate onchocerciasis (river blindness). This study used an integrated approach to identify adult female Onchocerca volvulus antigens that can be explored for developing serodiagnostic tests. The first step was to develop a detailed multi-omics database of all O. volvulus proteins deduced from the genome, gene transcription data for different stages of the parasite including eight individual female worms (providing gene expression information for 94.8% of all protein coding genes), and the adult female worm proteome (detecting 2126 proteins). Next, female worm proteins were purified with IgG antibodies from onchocerciasis patients and identified using LC-MS with a high-resolution hybrid quadrupole-time-of-flight mass spectrometer. A total of 241 immunoreactive proteins were identified among those bound by IgG from infected individuals but not IgG from uninfected controls. These included most of the major diagnostic antigens described over the past 25 years plus many new candidates. Proteins of interest were prioritized for further study based on a lack of conservation with orthologs in the human host and other helminthes, their expression pattern across the life cycle, and their consistent expression among individual female worms. Based on these criteria, we selected 33 proteins that should be carried forward for testing as serodiagnostic antigens to supplement existing diagnostic tools. These candidates, together with the extensive pan-omics dataset generated in this study are available to the community (http://nematode.net) to facilitate basic and translational research on onchocerciasis.

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts.

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Recommendations for the Generation, Quantification, Storage, and Handling of Peptides Used for Mass Spectrometry-Based Assays.

BACKGROUND: For many years, basic and clinical researchers have taken advantage of the analytical sensitivity and specificity afforded by mass spectrometry in the measurement of proteins. Clinical laboratories are now beginning to deploy these work flows as well. For assays that use proteolysis to generate peptides for protein quantification and characterization, synthetic stable isotope-labeled internal standard peptides are of central importance. No general recommendations are currently available surrounding the use of peptides in protein mass spectrometric assays. CONTENT: The Clinical Proteomic Tumor Analysis Consortium of the National Cancer Institute has collaborated with clinical laboratorians, peptide manufacturers, metrologists, representatives of the pharmaceutical industry, and other professionals to develop a consensus set of recommendations for peptide procurement, characterization, storage, and handling, as well as approaches to the interpretation of the data generated by mass spectrometric protein assays. Additionally, the importance of carefully characterized reference materials-in particular, peptide standards for the improved concordance of amino acid analysis methods across the industry-is highlighted. The alignment of practices around the use of peptides and the transparency of sample preparation protocols should allow for the harmonization of peptide and protein quantification in research and clinical care.

Targeted peptide measurements in biology and medicine: best practices for mass spectrometry-based assay development using a fit-for-purpose approach.

Adoption of targeted mass spectrometry (MS) approaches such as multiple reaction monitoring (MRM) to study biological and biomedical questions is well underway in the proteomics community. Successful application depends on the ability to generate reliable assays that uniquely and confidently identify target peptides in a sample. Unfortunately, there is a wide range of criteria being applied to say that an assay has been successfully developed. There is no consensus on what criteria are acceptable and little understanding of the impact of variable criteria on the quality of the results generated. Publications describing targeted MS assays for peptides frequently do not contain sufficient information for readers to establish confidence that the tests work as intended or to be able to apply the tests described in their own labs. Guidance must be developed so that targeted MS assays with established performance can be made widely distributed and applied by many labs worldwide. To begin to address the problems and their solutions, a workshop was held at the National Institutes of Health with representatives from the multiple communities developing and employing targeted MS assays. Participants discussed the analytical goals of their experiments and the experimental evidence needed to establish that the assays they develop work as intended and are achieving the required levels of performance. Using this "fit-for-purpose" approach, the group defined three tiers of assays distinguished by their performance and extent of analytical characterization. Computational and statistical tools useful for the analysis of targeted MS results were described. Participants also detailed the information that authors need to provide in their manuscripts to enable reviewers and readers to clearly understand what procedures were performed and to evaluate the reliability of the peptide or protein quantification measurements reported. This paper presents a summary of the meeting and recommendations.

Wavelet-based peak detection and a new charge inference procedure for MS/MS implemented in ProteoWizard's msConvert.

We report the implementation of high-quality signal processing algorithms into ProteoWizard, an efficient, open-source software package designed for analyzing proteomics tandem mass spectrometry data. Specifically, a new wavelet-based peak-picker (CantWaiT) and a precursor charge determination algorithm (Turbocharger) have been implemented. These additions into ProteoWizard provide universal tools that are independent of vendor platform for tandem mass spectrometry analyses and have particular utility for intralaboratory studies requiring the advantages of different platforms convergent on a particular workflow or for interlaboratory investigations spanning multiple platforms. We compared results from these tools to those obtained using vendor and commercial software, finding that in all cases our algorithms resulted in a comparable number of identified peptides for simple and complex samples measured on Waters, Agilent, and AB SCIEX quadrupole time-of-flight and Thermo Q-Exactive mass spectrometers. The mass accuracy of matched precursor ions also compared favorably with vendor and commercial tools. Additionally, typical analysis runtimes (∼1-100 ms per MS/MS spectrum) were short enough to enable the practical use of these high-quality signal processing tools for large clinical and research data sets.